A process-tolerant cache architecture for improved yield in nanoscale technologies

Authors:
Amit Agarwal;Bipul C. Paul;Hamid Mahmoodi;Animesh Datta;Kaushik Roy
Affiliations:
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
2005

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Abstract

Process parameter variations are expected to be significantly high in a sub-50-nm technology regime, which can severely affect the yield, unless very conservative design techniques are employed. The parameter variations are random in nature and are expected to be more pronounced in minimum geometry transistors commonly used in memories such as SRAM. Consequently, a large number of cells in a memory are expected to be faulty due to variations in different process parameters. In this paper, we analyze the impact of process variation on the different failure mechanisms in SRAM cells. We also propose a process-tolerant cache architecture suitable for high-performance memory. This technique dynamically detects and replaces faulty cells by dynamically resizing the cache. It surpasses all the contemporary fault tolerant schemes such as row/column redundancy and error-correcting code (ECC) in handling failures due to process variation. Experimental results on a 64-K direct map L1 cache show that the proposed technique can achieve 94% yield compared to its original 33% yield (standard cache) in a 45-nm predictive technology under σVt-inter = σVt-intra = 30 mV.